In [3]:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import plotly.express as px

import plotly.graph_objects as go

from plotly.offline import init_notebook_mode, iplot

init_notebook_mode()

Choropleth map of europe's protected forests¶

In [4]:
protection= pd.read_csv(r'world protected forests procent.csv')
In [5]:
# format the numbers nicely
In [6]:
pd.options.display.float_format = '{:,.1f}'.format
pd.set_option('display.max_rows', None)
In [7]:
protection.head()
Out[7]:
Unnamed: 0 total forest area 2020 1000 ha % protected forest out fo total forest area % forest of total land area % all nature protected areas out of total surface
0 Finland 22409 16.7 73.7 13.3
1 Sweden 27980 8.1 68.7 14.5
2 Japan 17100 9.1 68.5 29.8
3 Montenegro 827 19.7 61.5 13.8
4 Brazil 519500 42.3 61.0 7.2

Data cleanup¶

In [8]:
protection= protection.rename(columns= {'Unnamed: 0': 'Country'})
In [9]:
protection.iloc[41,2]= 1
In [10]:
protection= protection.rename(columns= {'% protected forest out fo total forest area': '% protected forest out of total forest area'})
In [11]:
protection= protection.rename(columns= {'% protected forest out of total forest area': '% Protected Forest'})
protection= protection.rename(columns= {'total forest area 2020 1000 ha': 'Forest Area 2020 (1000 ha)'})
protection= protection.rename(columns= {'% forest of total land area': '% Forest'})
protection= protection.rename(columns= {'% all nature protected areas out of total surface': '% Protected Nature Areas'})

Read the geojson file of europe countries¶

  • find the common field which should be the country name
  • make sure all countries are written the same in both files
In [13]:
import json
import pandas as pd
import plotly.graph_objects as go
import geopandas as gpd
In [ ]:
In [14]:
europe_geojson = gpd.read_file("choropleth map protection\europe.geojson")
In [77]:
import os
file_size = os.path.getsize("choropleth map protection\europe.geojson")
file_size_MB = file_size / (1024 * 1024)

print(f"File size: {file_size_MB:.2f} MB")
file_size

File size: 4.58 MB
Out[77]:
4804689
In [15]:
europe_geojson.head()
Out[15]:
featurecla scalerank labelrank sovereignt sov_a3 adm0_dif level type tlc admin ... fclass_id fclass_pl fclass_gr fclass_it fclass_nl fclass_se fclass_bd fclass_ua filename geometry
0 Admin-0 country 0 5 Lithuania LTU 0 2 Sovereign country 1 Lithuania ... NaN NaN NaN NaN NaN NaN NaN NaN LTU.geojson MULTIPOLYGON (((26.59453 55.66699, 26.60383 55...
1 Admin-0 country 0 5 Latvia LVA 0 2 Sovereign country 1 Latvia ... NaN NaN NaN NaN NaN NaN NaN NaN LVA.geojson POLYGON ((27.35293 57.52760, 27.52817 57.52848...
2 Admin-0 country 0 4 Belarus BLR 0 2 Sovereign country 1 Belarus ... NaN NaN NaN NaN NaN NaN NaN NaN BLR.geojson POLYGON ((23.60624 51.51740, 23.60231 51.53078...
3 Admin-0 country 0 5 Czechia CZE 0 2 Sovereign country 1 Czechia ... NaN NaN NaN NaN NaN NaN NaN NaN CZE.geojson POLYGON ((14.81039 50.85845, 14.83168 50.85798...
4 Admin-0 country 0 2 Germany DEU 0 2 Sovereign country 1 Germany ... NaN NaN NaN NaN NaN NaN NaN NaN DEU.geojson MULTIPOLYGON (((13.81572 48.76643, 13.78586 48...

5 rows × 170 columns

In [16]:
protection['Country'].unique()
Out[16]:
array(['Finland', 'Sweden', 'Japan', 'Montenegro', 'Brazil', 'Slovenia',
       'Estonia', 'Latvia', 'Russian Federation', 'Austria', 'Belarus',
       'Bosnia and Herzegovina', 'Liechtenstein', 'Georgia',
       'Slovak Republic', 'Norway', 'Spain', 'Luxembourg', 'Portugal',
       'United States', 'Bulgaria', 'Lithuania', 'Croatia',
       'Czech Republic', 'Andorra', 'Italy', 'Germany', 'Switzerland',
       'France', 'Serbia', 'Poland', 'Greece', 'Romania', 'Turkiye',
       'Albania', 'Belgium', 'Hungary', 'Cyprus', 'Ukraine', 'Denmark',
       'United Kingdom', 'Moldova', 'Ireland', 'Netherlands', 'Malta',
       'Iceland', 'Monaco'], dtype=object)

Some cleanup necessary for both files to match¶

In [17]:
protection['Country']= protection['Country'].str.replace('Czech Republic', 'Czechia')
In [18]:
protection['Country']= protection['Country'].str.replace('Bosnia and Herzegovina', 'Bosnia and Herz.')
In [19]:
protection['Country']= protection['Country'].str.replace('Turkiye', 'Turkey')
protection['Country']= protection['Country'].str.replace('Russian Federation', 'Russia')
In [20]:
protection['Country']= protection['Country'].str.replace('Slovak Republic', 'Slovakia')
protection['Country']= protection['Country'].str.replace('Russian Federation', 'Russia')
In [21]:
list(set(list(europe_geojson['name'].unique())) - set(list(protection['Country'])))
Out[21]:
['Guernsey',
 'North Macedonia',
 'Kosovo',
 'Jersey',
 'Isle of Man',
 'Åland',
 'Faeroe Is.',
 'San Marino',
 'Gibraltar',
 'Vatican']
In [22]:
list(set(list(protection['Country']))- set(list(europe_geojson['name'].unique())) )
Out[22]:
['Cyprus', 'Brazil', 'Georgia', 'Turkey', 'United States', 'Japan']
In [23]:
import json
back_geojson = europe_geojson.to_json()
j = json.loads(back_geojson)
In [26]:
#fill in missing data
protection.loc[1, '% Protected Forest']= 6.8
In [27]:
# check countries which are in one file but not in the other
list(set(list(europe_geojson['name'].unique())) - set(list(protection['Country'])))
Out[27]:
['Guernsey',
 'North Macedonia',
 'Kosovo',
 'Jersey',
 'Isle of Man',
 'Åland',
 'Faeroe Is.',
 'San Marino',
 'Gibraltar',
 'Vatican']
In [28]:
protection.loc[47]= protection.loc[46]
protection.loc[48]= protection.loc[46]
In [29]:
protection.iloc[47, 0]= 'Kosovo'
protection.iloc[47, 1]= 1089
protection.iloc[47, 3]= 44.7
protection.iloc[47, 2]= 42.6
protection.iloc[47, 4]= 4.39

protection.iloc[48, 0]= 'North Macedonia'
protection.iloc[48, 1]= 989
protection.iloc[48, 3]= 38.5
protection.iloc[48, 2]= 13.1
protection.iloc[48, 4]= 8.9
In [25]:
# europe_geojson = gpd.read_file("choropleth map protection\custom.geojson")
In [26]:
import json
back_geojson = europe_geojson.to_json()
j = json.loads(back_geojson)
In [ ]:
In [71]:
import pandas as pd
import plotly.graph_objects as go

# with open("file.geojson", "r", encoding="utf-8") as f:
#     geometry = geojson.load(f)
import plotly.express as px


fig = px.choropleth_mapbox(protection, geojson=j, locations='Country', color='% Forest',featureidkey="properties.name",
                           color_continuous_scale= [[0, 'rgb(254, 125, 74)'], [0.2, 'yellow'],[0.4, 'rgb(221, 247, 180)'], [1, 'green']],
#                            range_color=(0, 12),
#                            scope="europe",
#                     projection="hammer",
                           labels={'% Forest':'% Forest out of All Land'},
                          
                           mapbox_style="carto-positron",
                           zoom=3, center = {"lat": 58, "lon": 15},
                           opacity=0.7,
                           
                          )
fig.update_layout(autosize=True,
    width=900,
    height=900,
    margin=dict(
        l=10,
        r=10,
        b=100,
        t=100,
        pad=1))
fig.update_layout(
    title={
        'text': "<b>% Forest out of Total Land",
        'y':0.95,
        'x':0.45,
        'xanchor': 'center',
        'yanchor': 'top'})
fig.show()
In [ ]: